[go: up one dir, main page]
More Web Proxy on the site http://driver.im/

CN105260694A - Two-dimension code area locating method based on multistage backbone extraction and analysis - Google Patents

Two-dimension code area locating method based on multistage backbone extraction and analysis Download PDF

Info

Publication number
CN105260694A
CN105260694A CN201510705776.8A CN201510705776A CN105260694A CN 105260694 A CN105260694 A CN 105260694A CN 201510705776 A CN201510705776 A CN 201510705776A CN 105260694 A CN105260694 A CN 105260694A
Authority
CN
China
Prior art keywords
image
multistage
bar code
backbone
key
Prior art date
Legal status (The legal status is an assumption and is not a legal conclusion. Google has not performed a legal analysis and makes no representation as to the accuracy of the status listed.)
Granted
Application number
CN201510705776.8A
Other languages
Chinese (zh)
Other versions
CN105260694B (en
Inventor
王东
顾艳春
陈俊健
李晓东
Current Assignee (The listed assignees may be inaccurate. Google has not performed a legal analysis and makes no representation or warranty as to the accuracy of the list.)
Foshan University
Original Assignee
Foshan University
Priority date (The priority date is an assumption and is not a legal conclusion. Google has not performed a legal analysis and makes no representation as to the accuracy of the date listed.)
Filing date
Publication date
Application filed by Foshan University filed Critical Foshan University
Priority to CN201510705776.8A priority Critical patent/CN105260694B/en
Publication of CN105260694A publication Critical patent/CN105260694A/en
Application granted granted Critical
Publication of CN105260694B publication Critical patent/CN105260694B/en
Expired - Fee Related legal-status Critical Current
Anticipated expiration legal-status Critical

Links

Landscapes

  • Image Analysis (AREA)
  • Length Measuring Devices By Optical Means (AREA)

Abstract

A two-dimension code area locating method based on multistage backbone extraction and analysis of the invention comprises the steps of image preprocessing, image background color level filtering, image filtering, image binarization, preliminary barcode locating, and accurate barcode locating. The method is of wide applicability. The method can be applicable to files of a variety of popular image formats, supports files of a variety of color patterns such as color map, grey-scale map and black-and-white map, and can be used to recognize two-dimension code images of various forms. The method can adapt to a variety of light conditions, and can well self-adapt to different brightness and exposure conditions. With the method, the background color level range can be analyzed automatically, and the influence of the background image on barcode location can be eliminated effectively. The method has good robustness to rotation and noise, and can well resist the influence of environmental noise. The method is of high location success rate and accuracy and low rate of false reporting. Through a multistage backbone extraction approach, the computational complexity is effectively reduced, and location is fast.

Description

A kind of two-dimension code area localization method extracting based on multistage backbone and analyze
Technical field
The present invention relates to a kind of localization method of two-dimensional bar code, especially the localization method of QRCode two-dimensional bar code, specifically, relate to a kind of two-dimension code area localization method extracting based on multistage backbone and analyze.
Background technology
Bar code is a kind of printable computerese, is also automatic identification technology the most economic and practical up to now.Compared with bar code, two-dimensional bar code has the advantages such as the error correcting capability that information capacity is large, coding range is wide, message density is high, it is little to take up room, damage-retardation ability is strong and good, pays close attention to widely so two-dimensional bar code obtains and applies.
Two-dimensional bar code conventional in the world has two kinds, and one is stack (2DStackedCode), namely form is to be laminated, as Code16K, Code49, PDF417 etc. by the height brachymemma of bar code again; Another kind is matrix form (2DMatrixCode), namely form with a matrix type, the appearance that matrix respective element position is put represents binary one, there is not expression binary zero in that puts, the permutation and combination of point determines the meaning representated by matrix two-dimensional barcode, as MaxiCode, QRCode, DataMatrix etc.Wherein, QRCode is first and clearly defines and publish the two-dimensional bar code of coding criterion, is also the most widely used two-dimensional bar code.
Both at home and abroad for the location of two-dimensional bar code, there are the edge extracting based on edge gradient direction, the Bar code positioning based on Run-Length Coding thought and the classical way such as location based on mathematical morphological operation and Canny rim detection.First these methods carry out pre-service to bar code image, then above-mentioned algorithm principle is utilized to carry out bar code region segmentation and the extraction of feature quadrilateral, and do precision process on this basis, thus obtain the characteristic parameter in bar code region, realize the detection and positioning of bar code.
Existing method process background and be comparatively simple and the picture of two-dimensional bar code comparatively rule time, achieve good effect.But in real life, the two-dimensional barcode image collected by absorption equipment, is usually had the noises such as stained containing on bright and dark light inequality, collecting device or two-dimensional barcode image, also has background patterns too complicated, causes the interference being difficult to distinguish.And relative to the two-dimensional barcode image of standard, the situation of the geometry deformations such as the image collected often has rotation, mistake is cut, distortion occurs.These phenomenons usually cause existing Bar code positioning method deleterious even complete failure.Meanwhile, the problem that existing method ubiquity location more efficiency consuming time is lower.Therefore, the Quick Response Code localization method that research is quick and precisely adapted under multiple environment seems very important.
Summary of the invention
The present invention is directed at bright and dark light uneven, two-dimensional barcode image there is stained noise of Denging, background patterns is too complicated, bar code place image has rotation, when mistake cuts the phenomenons such as geometry deformation, existing two-dimensional bar code localization method the deleterious even problem of complete failure, this patent proposes a kind of practical and two-dimensional bar code area positioning method efficiently, it effectively can solve the impact that light problem and noise problem are located for two-dimensional bar code, and for rotation, mistake the phenomenon such as to be cut and is had good robustness, and registration, in multiple environment, all there is higher locating accuracy, simultaneously, this method computing is quick, can meet for the higher occasion of requirement of real-time.
In order to solve the problems of the technologies described above, the present invention is achieved by the following technical solutions:
Extract and the two-dimension code area localization method analyzed based on multistage backbone, comprise the following steps:
1) Image semantic classification;
(1) image gray processing: because the image obtained is generally coloured image, for making process simplify, must chromatic information be projected in gray space;
(2) image background color range filtering: image background is positioned with certain interference and negative interaction to two-dimensional bar code, therefore, between recognition image background color range location and effectively filtering can improve efficiency and the accuracy of Bar code positioning.Image background color range has three features usually, and one is that color range distributed area is less, and two is that distribution density is higher, three be region, image border color range usually and background color range comparatively identical.For this reason, it is interval that this method takes subregion weighted statistical histogram to carry out background extraction color range, and utilize this interval efficiency to eliminate background;
(3) first image filtering: the image after gray processing mainly also exists the distortion such as edge burr, isolated point noise, therefore must remove these interference, carry out shaping to bar code image, thus improve the accuracy of decoding;
(4) image binaryzation: binaryzation is a kind of important method in Iamge Segmentation.Choosing of binary-state threshold is vital process in image binaryzation, directly determines the effect of image after binaryzation;
2) bar code Primary Location;
(1) multistage picture element density distribution is key extracts:
(2) key pixel statistics with histogram;
(3) the preliminary region of bar code is obtained according to statistic histogram result;
3) bar code is accurately located;
(1) the further precision barcode position of template matching method is adopted:
(2) rotation correction:
(3) bar code accurate location is obtained.
Further, the filtering of described image background color range is: first, image is divided into fringe region and zone line, and gives different weight to zones of different; Secondly, the grey level histogram after weighting is calculated; Subsequently, utilize statistics background extraction color range interval; Finally, utilize background color range interval that background is carried out effective filtering.
Further, described image filtering adopts medium filtering, and adopts rectification square window.
Further, the key extraction of described multistage picture element density distribution is: according to the order that window size is descending, arrange multistage moving window, extract key pixel in window, analyze key pixel distribution density, and carry out corrosion treatment to backbone.
Further, described key pixel statistics with histogram is: multistage backbone extract and corrosion treatment basis on, do the horizontal and vertical projection operation of pixel respectively, obtain the pixel distribution statistic histogram of key pixel.
Further, described according to the statistic histogram result acquisition preliminary region of bar code: key pixel statistics with histogram result is analyzed, obtain key outburst area, according to multistage key compression situation, the key outburst area obtained is mapped go back to original image space, and obtain the preliminary region of two-dimensional bar code
Compared with prior art, the invention has the beneficial effects as follows:
(1) this method has wider applicability.This method can be applicable to multiple popular image format file, as JPG, BMP etc.Meanwhile, support the multicolour schema files such as colour, gray-scale map, artwork master, the image in 2 D code of identifiable design various ways, is particularly useful for the location of QRCode two-dimensional bar code.
(2) this method has good robustness to illumination condition.This method can be adapted to multiple illumination condition, all can good self-adaptation to different light and shade and conditions of exposure.
(3) this method has good robustness to background image.This method energy automatic analysis background colour order range, and effectively eliminate the impact of background image for Bar code positioning.
(4) this method has good robustness to rotation and noise, and better can resist the impact of neighbourhood noise.
(5) this method two-dimensional bar code locating accuracy is high.This method has good position success rate and accuracy rate, and rate of false alarm is low.
(6) this method locating speed is fast.This method takes multistage key extracting mode to effectively reduce computation complexity, has locating speed faster.
Accompanying drawing explanation
Accompanying drawing is used to provide a further understanding of the present invention, together with embodiments of the present invention for explaining the present invention, is not construed as limiting the invention, in the accompanying drawings:
Fig. 1 is positioning flow figure of the present invention;
Fig. 2 is example 1 locating effect figure;
Fig. 3 is example 2 locating effect figure;
Fig. 4 is example 3 locating effect figure;
Fig. 5 is example 4 locating effect figure.
Embodiment
Below in conjunction with accompanying drawing, the preferred embodiments of the present invention are described, should be appreciated that preferred embodiment described herein is only for instruction and explanation of the present invention, is not intended to limit the present invention.
The image be input as containing two-dimensional bar code of this method, exports the coordinate into bar code region, also can intercept bar code region image easily, consult Fig. 1.
1. implementation process
(1) image containing two-dimensional bar code is read.Read the original image containing two-dimensional bar code, original image type can be JPG, BMP or other common format image files.
(2) original image gray processing.To original image gray processing.Gray processing computing formula is:
I=0.3R+0.59G+0.11B
Wherein, R, G, B are red, green, blue three-component respectively.
(3) image background color range filtering.Concrete mode is: first, image is divided into fringe region and zone line, and gives different weight to zones of different; Secondly, the grey level histogram after weighting is calculated; Subsequently, utilize statistics background extraction color range interval; Finally, utilize background color range interval that background is carried out effective filtering.
(4) image filtering.Medium filtering not only can reduce the interference of noise, and can retain the edge of image and sharp-pointed details preferably.Simultaneously because the basic module of bar code image is all squares, therefore adopt square window can obtain good effect when medium filtering.
(5) image binaryzation.By the gray-scale map after the filtering of background color range, again statistics of histogram is carried out to it, find out suitable two-value cut off value, and carry out binary conversion treatment accordingly.
(6) extract multistage backbone and do etching operation.Choose the moving window of different size, extract key pixel in window, add up and analyze key pixel distribution density, subsequently corrosion treatment being carried out to backbone.
(7) statistic histogram is generated to image backbone.Statistic histogram is generated from horizontal and vertical directions.
(8) the preliminary region of bar code is obtained.Analytic statistics histogram feature, finds out the preliminary region of bar code accordingly.The region now found out is approximate region, and therefore, selected region is larger.
(9) template matching method is utilized accurately to locate.Compared with original image, the preliminary region of bar code has reduced a lot, therefore considers to adopt template matching method accurately to locate.For QR, because QR two-dimensional bar code has three identification points, lay respectively at the upper left of bar code, lower-left and the upper right corner.Identification point has special ratio, and simultaneously under the effect of mask, the figure of such ratio can not appear in other positions in bar code region, so accurately can locate bar code by finding these three positions.
(10) rotation correction.Reanalyse the bar code image after accurately locating, can determine that bar code is the need of the angle rotated and rotate by the centre coordinate of the pixel projection feature in the preliminary region of bar code and identification point.
(11) the two-dimensional bar code position after precision is obtained and cut-away view picture.Precision correction barcode position, returns bar code regional location coordinate, also can directly intercept bar code area image.
2. example
[example 1] as shown in Figure 2.In example 1 original image, bar code region is comparatively obvious, and background is comparatively simple.Experimental result shows, and accurately can locate two-dimensional bar code.
[example 2] as shown in Figure 3.In example 2, original image background is comparatively complicated, and has the phenomenons such as certain selected angle and fold.Experimental result shows, and accurately can locate two-dimensional bar code.
[example 3] as shown in Figure 4.In example 3, original image have passed through certain stretching and distortion, and have passed through the rotation of 90 degree, and meanwhile, image exposure degree also has relatively big difference with example 1.Experimental result shows, and accurately can locate two-dimensional bar code.
[example 4] as shown in Figure 5.Example 4 is not containing two-dimensional bar code.Experimental result shows, and locates failure because finding two-dimensional bar code.
This method positioning result:
(1) according to test to 100 width images, this system Bar code positioning success ratio is 98%, and failure cause is mainly the impact for Bar code positioning of intensive word or the seal similar to bar code.
(2) in the zone marker that success is located, areal coverage (marked region contains the area/actual bar code region area * 100% of bar code) reaches more than 98%, and region flood rate (marked region is not containing the area/actual bar code region area * 100% of bar code) is less than 5%.
Locating speed:
Locating speed is very fast, as shown in table 1.Wherein, test environment is:
(1) CPU:IntelT6600, dominant frequency is 2.20GHz, double-core.
(2) internal memory: 2GB.
(3) operating system: Windows7.
Table 1 Bar code positioning expends time in table
Last it is noted that these are only the preferred embodiments of the present invention; be not limited to the present invention; although with reference to embodiment to invention has been detailed description; for a person skilled in the art; it still can be modified to the technical scheme described in foregoing embodiments; or equivalent replacement is carried out to wherein portion of techniques feature; but it is within the spirit and principles in the present invention all; any amendment of doing, equivalent replacement, improvement etc., all should be included within protection scope of the present invention.

Claims (6)

1. extract and the two-dimension code area localization method analyzed based on multistage backbone, it is characterized in that, comprise the following steps:
1) Image semantic classification;
(1) image gray processing;
(2) image background color range filtering;
(3) image filtering;
(4) image binaryzation;
2) bar code Primary Location;
(1) multistage picture element density distribution is key extracts:
(2) key pixel statistics with histogram;
(3) the preliminary region of bar code is obtained according to statistic histogram result;
3) bar code is accurately located;
(1) the further precision barcode position of template matching method is adopted:
(2) rotation correction:
(3) bar code accurate location is obtained.
2. a kind of based on multistage backbone's extraction and the two-dimension code area localization method analyzed according to claim 1, it is characterized in that, the filtering of described image background color range is: first, image is divided into fringe region and zone line, and gives different weight to zones of different; Secondly, the grey level histogram after weighting is calculated; Subsequently, utilize statistics background extraction color range interval; Finally, utilize background color range interval that background is carried out effective filtering.
3. a kind of according to claim 1 based on multistage backbone's extraction and the two-dimension code area localization method analyzed, it is characterized in that, described image filtering adopts medium filtering, and adopts rectification square window.
4. a kind of based on multistage backbone's extraction and the two-dimension code area localization method analyzed according to claim 1, it is characterized in that, the key extraction of described multistage picture element density distribution is: according to the order that window size is descending, multistage moving window is set, extract key pixel in window, analyze key pixel distribution density, and corrosion treatment is carried out to backbone.
5. a kind of based on multistage backbone's extraction and the two-dimension code area localization method analyzed according to claim 1, it is characterized in that, described key pixel statistics with histogram is: multistage backbone extract and corrosion treatment basis on, do the horizontal and vertical projection operation of pixel respectively, obtain the pixel distribution statistic histogram of key pixel.
6. a kind of based on multistage backbone's extraction and the two-dimension code area localization method analyzed according to claim 1, it is characterized in that, described according to the statistic histogram result acquisition preliminary region of bar code: key pixel statistics with histogram result is analyzed, obtain key outburst area, according to multistage key compression situation, the key outburst area obtained is mapped go back to original image space, and obtain the preliminary region of two-dimensional bar code.
CN201510705776.8A 2015-10-22 2015-10-22 A kind of two-dimension code area localization method based on multistage key extraction with analysis Expired - Fee Related CN105260694B (en)

Priority Applications (1)

Application Number Priority Date Filing Date Title
CN201510705776.8A CN105260694B (en) 2015-10-22 2015-10-22 A kind of two-dimension code area localization method based on multistage key extraction with analysis

Applications Claiming Priority (1)

Application Number Priority Date Filing Date Title
CN201510705776.8A CN105260694B (en) 2015-10-22 2015-10-22 A kind of two-dimension code area localization method based on multistage key extraction with analysis

Publications (2)

Publication Number Publication Date
CN105260694A true CN105260694A (en) 2016-01-20
CN105260694B CN105260694B (en) 2017-12-01

Family

ID=55100376

Family Applications (1)

Application Number Title Priority Date Filing Date
CN201510705776.8A Expired - Fee Related CN105260694B (en) 2015-10-22 2015-10-22 A kind of two-dimension code area localization method based on multistage key extraction with analysis

Country Status (1)

Country Link
CN (1) CN105260694B (en)

Cited By (8)

* Cited by examiner, † Cited by third party
Publication number Priority date Publication date Assignee Title
CN106250833A (en) * 2016-07-22 2016-12-21 深圳棒棒帮科技有限公司 The generation method of micrographics group and the recognition methods of micro-figure group for information MAP
CN106295443A (en) * 2016-08-03 2017-01-04 浙江华睿科技有限公司 The localization method in a kind of bar code region and device
CN110245538A (en) * 2019-06-26 2019-09-17 北京慧眼智行科技有限公司 A kind of horizontal and vertical parity check code localization method and system
CN110263595A (en) * 2019-06-25 2019-09-20 北京慧眼智行科技有限公司 A kind of two dimensional code detection method and device
CN110276226A (en) * 2019-06-26 2019-09-24 北京慧眼智行科技有限公司 A kind of dot matrix code detection method and system
CN110287752A (en) * 2019-06-25 2019-09-27 北京慧眼智行科技有限公司 A kind of dot matrix code detection method and device
CN110736965A (en) * 2018-10-18 2020-01-31 武汉卫思德科技有限公司 two-dimensional coding and decoding method for visible light positioning
CN112598095A (en) * 2020-12-11 2021-04-02 厦门市美亚柏科信息股份有限公司 High-density two-dimensional code data transmission method and device and storage medium

Citations (5)

* Cited by examiner, † Cited by third party
Publication number Priority date Publication date Assignee Title
CN103870790A (en) * 2014-04-02 2014-06-18 胡建国 Recognition method and device of two-dimensional bar code
CN103914675A (en) * 2014-03-17 2014-07-09 东华大学 Garment QD code recognition method
CN104573674A (en) * 2015-01-29 2015-04-29 杨克己 1D (one-dimensional) barcode recognition for real-time embedded system
CN104680109A (en) * 2013-12-03 2015-06-03 航天信息股份有限公司 Image recognition-based location method for bar code area
CN104866849A (en) * 2015-04-30 2015-08-26 天津大学 Food nutrition label identification method based on mobile terminal

Patent Citations (5)

* Cited by examiner, † Cited by third party
Publication number Priority date Publication date Assignee Title
CN104680109A (en) * 2013-12-03 2015-06-03 航天信息股份有限公司 Image recognition-based location method for bar code area
CN103914675A (en) * 2014-03-17 2014-07-09 东华大学 Garment QD code recognition method
CN103870790A (en) * 2014-04-02 2014-06-18 胡建国 Recognition method and device of two-dimensional bar code
CN104573674A (en) * 2015-01-29 2015-04-29 杨克己 1D (one-dimensional) barcode recognition for real-time embedded system
CN104866849A (en) * 2015-04-30 2015-08-26 天津大学 Food nutrition label identification method based on mobile terminal

Cited By (12)

* Cited by examiner, † Cited by third party
Publication number Priority date Publication date Assignee Title
CN106250833A (en) * 2016-07-22 2016-12-21 深圳棒棒帮科技有限公司 The generation method of micrographics group and the recognition methods of micro-figure group for information MAP
CN106250833B (en) * 2016-07-22 2019-11-19 深圳棒棒帮科技有限公司 The recognition methods of the generation method of micrographics group for information MAP and micro- figure group
CN106295443A (en) * 2016-08-03 2017-01-04 浙江华睿科技有限公司 The localization method in a kind of bar code region and device
CN106295443B (en) * 2016-08-03 2018-12-07 浙江华睿科技有限公司 A kind of localization method and device in bar code region
CN110736965A (en) * 2018-10-18 2020-01-31 武汉卫思德科技有限公司 two-dimensional coding and decoding method for visible light positioning
CN110263595A (en) * 2019-06-25 2019-09-20 北京慧眼智行科技有限公司 A kind of two dimensional code detection method and device
CN110287752A (en) * 2019-06-25 2019-09-27 北京慧眼智行科技有限公司 A kind of dot matrix code detection method and device
CN110263595B (en) * 2019-06-25 2023-02-17 北京慧眼智行科技有限公司 Two-dimensional code detection method and device
CN110245538A (en) * 2019-06-26 2019-09-17 北京慧眼智行科技有限公司 A kind of horizontal and vertical parity check code localization method and system
CN110276226A (en) * 2019-06-26 2019-09-24 北京慧眼智行科技有限公司 A kind of dot matrix code detection method and system
CN112598095A (en) * 2020-12-11 2021-04-02 厦门市美亚柏科信息股份有限公司 High-density two-dimensional code data transmission method and device and storage medium
CN112598095B (en) * 2020-12-11 2023-01-24 厦门市美亚柏科信息股份有限公司 High-density two-dimensional code data transmission method and device and storage medium

Also Published As

Publication number Publication date
CN105260694B (en) 2017-12-01

Similar Documents

Publication Publication Date Title
CN105260694A (en) Two-dimension code area locating method based on multistage backbone extraction and analysis
CN105335744B (en) A kind of one-dimension code zone location extracting band distribution characteristics based on image backbone
CN105069394B (en) Quick Response Code weighted average gray level method coding/decoding method and system
CN102096821B (en) Number plate identification method under strong interference environment on basis of complex network theory
Ashtari et al. An Iranian license plate recognition system based on color features
CN105260693A (en) Laser two-dimensional code positioning method
US8515162B2 (en) QR code processing method and apparatus thereof
CN101122953B (en) Picture words segmentation method
CN100456314C (en) QR two-dimensional bar code recognition method based on pickup head for chatting
CN106960208B (en) Method and system for automatically segmenting and identifying instrument liquid crystal number
CN102708351B (en) Method for fast identifying Data Matrix two-dimensional bar code under complicated working condition background
CN103942797B (en) Scene image text detection method and system based on histogram and super-pixels
US9177188B2 (en) Method and system for detecting detection patterns of QR code
CN104361336A (en) Character recognition method for underwater video images
CN103295013A (en) Pared area based single-image shadow detection method
CN106709500B (en) Image feature matching method
CN109190742B (en) Decoding method of coding feature points based on gray feature
Suran QR Code Image Correction based on Corner Detection and Convex Hull Algorithm.
CN105574486A (en) Image table character segmenting method
US7980473B2 (en) Camera based code reading
CN107563301A (en) Red signal detection method based on image processing techniques
Huang et al. Text detection and recognition in natural scene images
CN111401364B (en) License plate positioning algorithm based on combination of color features and template matching
CN108734131A (en) A kind of traffic sign symmetry detection methods in image
CN112528740A (en) Pressing plate state identification method

Legal Events

Date Code Title Description
C06 Publication
PB01 Publication
C10 Entry into substantive examination
SE01 Entry into force of request for substantive examination
GR01 Patent grant
GR01 Patent grant
CF01 Termination of patent right due to non-payment of annual fee
CF01 Termination of patent right due to non-payment of annual fee

Granted publication date: 20171201

Termination date: 20201022